1. Field of the Invention
The present invention relates to an ink jet printing apparatus and a calibration method. More specifically it relates to a printing apparatus with a calibration function to correct color deviations and also to a calibration method.
2. Description of the Related Art
As one output device to print an image on a variety of print media, such as paper, an ink jet printing apparatus is known. In recent years the ink jet printing apparatus has technologically advanced to be able to produce relatively high quality images and thus has come to be used not only for personal printing purpose but also as industrial printing apparatus that produce printed products to be sold as merchandise. So, demands not only for higher image quality of printed images but for improved reproducibility of images are growing year by year and there is also increasing calls for improvements in correcting even slight color deviations or density deviations.
An ink jet printing apparatus of this kind has been known to have a plurality of print heads or a plurality of nozzle arrays (arrays of ejection openings) for the same ink color. This construction enables bidirectional printing, which causes the print heads to print as they move in both forward and backward directions to improve printing speed, and can also prevent color variations of printed images caused by the bidirectional printing. In such a printing apparatus with a plurality of print heads or a plurality of nozzle arrays, however, a desired color of a printed image may not be produced because of variations in ink ejection characteristics among individual print heads or among individual nozzle arrays. Among factors contributing to the ink ejection characteristic variations among print heads or among nozzle arrays are structural variations among ink ejection energy generation elements or among ink ejection nozzles. For example, when electrothermal conversion elements (heaters) are used as the ejection energy generation elements, the factors contributing to the ink ejection characteristic variations include variations in the amount of generated heat among heaters (variations in the film thickness of heaters) and variations in ink ejection opening diameter among nozzles, of which the ink ejection openings form a part. Further, generated heat variations of heaters due to age deterioration and ink viscosity variations due to different environments where ink is used may cause changes in ink ejection volume, resulting in changes in printing characteristics of images.
Calibration is a known technology to deal with color differences caused by ink ejection characteristic variations among nozzle arrays or among print heads. Such calibration technology, for example, changes a γ table used in a γ correction processing as part of the image processing to correct the ink ejection characteristics of print heads. More specifically, this involves printing patches on a print medium by using a plurality of print heads or a plurality of nozzle arrays and, based on the printed patches, changing the γ table used in the γ correction processing to an appropriate setting. Methods for detecting color deviations of the printed patches include a visual check method and a method using an input device such as a scanner.
The visual method, for example, is known to print tertiary patches using three color inks (3 colorants)—C (cyan), M (magenta) and Y (yellow)—to examine the printed patches for color deviations. This method prints tertiary color patches by using C, M, Y inks at a ratio expected to produce an achromatic color and also prints a plurality of patches of almost gray by progressively changing application volumes of these inks. Then, by visually selecting a patch closest to achromatic color from the printed patches, print characteristics of C, M, Y inks are detected (Japanese Patent Laid-Open No. 10-278311).
The input device-based method using, for example, a scanner first prints patches for each of four ink colors—C (cyan), M (magenta), Y (yellow) and K (black)—and reads these patches with the scanner, colorimeter or density meter. It then detects a difference between a reading of each patch and an expected value of that patch and, based on the detected difference, changes a correction value such as γ value to correct colors of a printed image (Japanese Patent No. 2,661,917). There is another method that improves calibration precision by printing two types of patches—solid patterns (solid images) and gradation patterns of C, M, Y, K. Still another method to improve the calibration precision involves printing patches of a secondary color and a tertiary color using C, M, Y, K inks.
Further, a so-called serial scan type printing apparatus has a scanner or optical sensor mounted on a carriage on a printing apparatus body side to read patches. In the printing apparatus body, densities of printed patches are measured for automatic calibration (Japanese Patent Laid-Open No. 2004-167947). In such a printing apparatus, a scanner head to read patches and a print head to eject a plurality of different inks are mounted on a carriage. Upon receiving a calibration execution command, the printing apparatus prints patches on a print medium by ejecting inks of different colors from a print head and measures densities of the patches to calculate a difference (density difference) between a target value of print density and a measured value for each gradation level of each ink color. In this way, a density correction value can be determined for each gradation level of each ink color.
In a printing apparatus having a plurality of print heads or a plurality of nozzle arrays that eject the same color ink, the following method is available to generate binary data corresponding to each nozzle array. The method involves decomposing image data (R, G, B data) generated by a host system (including a host apparatus) into multi-valued data for each ink color and distributing the multi-valued data of the same color ink among a plurality of nozzle arrays before they are binarized. Consider, for example, a case where C (cyan) and M (magenta) ink are each assigned two nozzle arrays (C1, C2 nozzle arrays and M1, M2 nozzle arrays) and where Y (yellow) and K (black) ink are each assigned one nozzle array. In this case, C and M multi-valued data are distributed to the nozzle arrays C1, C2 and nozzle arrays M1, M2, respectively. Then, the distributed multi-valued data for C and M, the multi-valued data for Y and the multi-valued data for K are subjected to the image processing. That is, the multi-valued data distributed to each nozzle array undergoes the γ correction processing using the corresponding table and then the binarization processing for each nozzle array.
In this case, however, since the multi-valued data before binarization is distributed, a complementary relation among a plurality of nozzle arrays of the same ink may not be maintained when the multi-valued data is binarized. To cope with this problem, it is conceivable to keep the complementary relation among nozzle arrays as the multi-valued data for individual nozzle arrays are binarized. This method, however, makes the processing more complex and requires a large amount of memory, increasing the time taken by the processing.
Such image processing poses a similar problem also when the calibration is executed. That is, during the calibration a γ correction table corresponding to each of the nozzle arrays that eject the same color ink is updated. So, when the multi-valued data is binarized according to the updated γ correction table, the complementary relation among the nozzle arrays may not be maintained. Keeping the complementary relation among the nozzle arrays as the multi-valued data for the individual nozzle arrays are binarized will pose a problem of complicating the processing as described above.
Another conceivable method for generating binary data for each nozzle array may involve subjecting image data received from a host system to the image processing (including a color conversion processing or a γ correction processing) to binarized it and distribute the binarized data to individual nozzle arrays. However, the color deviation correction by the γ correction must be performed on the multi-valued data, not on the binarized data. So, the binarized data distributed to individual nozzle arrays needs to be converted into multi-valued data, subjected to the color deviation correction and then binarized again. In that case, because a complicated process of converting the binary data into multi-valued data and then binarizing the multi-valued data again is required, the processing becomes complex. Further, since this method also is required to binarize the multi-valued data for each nozzle array, the processing becomes complicated if the complementary relation among the nozzle arrays is to be kept while the multi-valued data for individual nozzle arrays are binarized.